Social interactions between people drive the spread of many infectious disease, including influenza, measles and tuberculosis. Consequently, they form the basis of many public health interventions, such as quarantine and contact tracing. However, quantitative approaches to understand social mixing and its role in transmission are poorly developed – only recently have efforts been made to quantify interaction patterns at a nationally-representative scale using egocentric sampling (Mossong 2008 PLoS Med). There is a gap between the social interaction data collected and the information required to explain infection incidence patterns. Closing this gap requires an improved understanding of the factors that influence social mixing patterns and the extent to which interaction information is necessary for epidemic forecasting and assessment of public health control (Read 2012 Epidem Infect).

Detailed social interaction information collected by Read and colleagues as part of the FluScape study (NIH/Wellcome) in southern China will be available to analyse. Social interaction, travel and demographic information have been collected annually from more than 2,000 individuals across a 4-year period (Jiang 2016 Int J Epidem). Additionally, antibody titres against a panel of influenza strains have also been collected annually from the cohort (Lessler 2012 PLoS Path). These data represent a unique opportunity to disentangle the social processes driving infection within urban and rural communities, with broad relevance to other populations and the potential to identify novel public health interventions.

This PhD will provide a student with the opportunity to lead the development of statistical methods and model fitting for health science, and establish themselves as a leading expert in social interaction and transmission modelling – a specialism increasingly required for national disease control and international eradication programmes. Potential research questions the PhD can address:
Q1. How can spatially-embedded networks of interaction be inferred from egocentric sampled information?
Q2. What demographic characteristics are associated with social interaction patterns?
Q3. What are the social network and demographic determinants of influenza infection?

For further information about the project, please contact either project supervisor: Dr Jonathan Read (jonathan.read@lancaster.ac.uk) or Dr Chris Jewell (c.jewell@lancaster.ac.uk)

Applications are made by completing an application for PhD Statistics and Epidemiology October 2019 through our online application system. Closing date: midnight 15th March 2019.

Funding Notes
Awards are available for UK or EU students only for a maximum of three years full-time study. Awards will cover University Tuition Fees and stipend at Research Council Doctoral Stipend Level (2018-2019: £14,777).